Implementasi ETL untuk Menghasilkan Fact Table Penjualan pada Data Warehouse Menggunakan Pentaho Data Integration
DOI:
https://doi.org/10.67142/edutik.v6i4.516Keywords:
ETL, Fact Table, Data Warehouse, Pentaho Data Integration, PenjualanAbstract
ABSTRAK
Pertumbuhan volume data transaksi penjualan mendorong kebutuhan sistem pengelolaan data yang mampu mengintegrasikan berbagai sumber ke dalam satu repositori terpusat untuk analisis bisnis. Penelitian ini bertujuan menerapkan mekanisme Extract, Transform, Load (ETL) serta membangun fact table penjualan dalam lingkungan data warehouse menggunakan Pentaho Data Integration (PDI). Tahapan pengembangan mencakup enam tahapan: (1) pengumpulan data transaksi penjualan, (2) perancangan skema data warehouse berbasis star schema, (3) ekstraksi data dari source database menggunakan komponen Table Input, (4) transformasi data melalui mekanisme Sort Rows, Select Values, dan Stream Lookup untuk membangun delapan tabel dimensi serta fact table, (5) pemuatan data ke dalam dimension table dan fact table menggunakan Table Output, serta (6) pengujian dan validasi konsistensi data antara source database dan data warehouse. Hasil implementasi menunjukkan bahwa proses ETL menggunakan PDI berhasil membangun delapan tabel dimensi, yaitu dimensi produk, kategori, kota, harga satuan, jumlah terjual, total penjualan, metode pembayaran, dan waktu, serta satu fact table penjualan yang mengintegrasikan seluruh dimensi melalui mekanisme Stream Lookup dengan pendekatan star schema. Berdasarkan temuan tersebut, disimpulkan bahwa penerapan ETL dan fact table penjualan menggunakan Pentaho Data Integration terbukti mampu mengoptimalkan tata kelola data sekaligus membangun infrastruktur data warehouse yang andal sebagai landasan pelaporan dan analisis data penjualan.
ABSTRACT
The growing volume of sales transaction data drives the need for a data management system capable of integrating multiple sources into a centralized repository for business analysis. This study aims to implement an Extract, Transform, Load (ETL) mechanism and construct a sales fact table within a data warehouse environment using Pentaho Data Integration (PDI). The development process encompasses six phases: (1) sales transaction data collection, (2) data warehouse schema design based on a star schema, (3) data extraction from the source database using the Table Input component, (4) data transformation through Sort Rows, Select Values, and Stream Lookup mechanisms to build eight dimension tables and a fact table, (5) data loading into each dimension table and fact table using Table Output, and (6) testing and validation of data consistency between the source database and the data warehouse. Implementation results demonstrate that the ETL process using PDI successfully constructed eight dimension tables, namely product, category, city, unit price, quantity sold, total sales, payment method, and time dimensions, along with one sales fact table integrating all dimensions through the Stream Lookup mechanism with a star schema approach. Based on these findings, it is concluded that the implementation of ETL and a sales fact table using Pentaho Data Integration proves capable of optimizing data governance while establishing a reliable data warehouse infrastructure as the foundation for sales data reporting and analysis.
Downloads
References
Andriansyah, D. (2022). Implementasi Extract-Transform-Load (ETL) Data Warehouse Laporan Harian Pool. Jurnal Teknik Informatika STMIK Antar Bangsa, 8(2), 45-49.
Badiuzzaman Biplob, M., & Mokammel Haque, M. (2021, December). Development of an efficient etl technique for data warehouses. In Proceedings of the International Conference on Big Data, IoT, and Machine Learning: BIM 2021 (pp. 243-255). Singapore: Springer Singapore.
Barahama, A. D., & Wardani, R. (2021, March). Data analysis and data warehouse design based on Pentaho data integration (kettle) to support the determination of student learning achievement. In IOP Conference Series: Materials Science and Engineering (Vol. 1098, No. 5, p. 052089). IOP Publishing.
Barahama, A. D., & Wardani, R. (2021, November). Utilization extract, transform, load for developing data warehouse in education using Pentaho Data Integration. In Journal of Physics: Conference Series (Vol. 2111, No. 1, p. 012030). IOP Publishing.
Dhaouadi, A., Bousselmi, K., Gammoudi, M. M., Monnet, S., & Hammoudi, S. (2022). Data warehousing process modeling from classical approaches to new trends: Main features and comparisons. Data, 7(8), 113.
Dinesh, L., & Devi, K. G. (2024). An efficient hybrid optimization of ETL process in data warehouse of cloud architecture. Journal of Cloud Computing, 13(1), 12.
Ghita, F., & Trisminingsih, R. (2021). Pengujian Data Warehouse SOLAP untuk Komoditas Pertanian Indonesia. Jurnal Ilmu Komputer dan Agri-Informatika, 8(1), 42-56.
Gueddoudj, E. Y., Chikh, A., & Attia, A. (2023). Os-ETL: A High-Efficiency, Open-Scala Solution for Integrating Heterogeneous Data in Large-Scale Data Warehousing. Ingénierie des Systèmes d'Information, 28(3).
Khan, B., Jan, S., Khan, W., & Chughtai, M. I. (2024). An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing. Journal on Big Data, 6.
Lelet, M., Kaparang, D. R., & Pratasik, S. (2023). Pengembangan Sistem Informasi Layanan Mahasiswa Fakultas Teknik Universitas Negeri Manado. Edutik: Jurnal Pendidikan Teknologi Informasi Dan Komunikasi, 3(1), 138-148.
Novandya, A. (2021). Data Warehouse: Fact Constellation Schema Dengan Pemodelan Data Dimensional Powell Pada Wedding Organizer. Reputasi: Jurnal Rekayasa Perangkat Lunak, 2(2), 59-65.
Pérez Garriga, A., Honrath, P., Wolking, S., Coldewey, B., Bozkir, S. A., May, P., ... & Lipprandt, M. (2024, August). Multi-Source Data ETL (Extract, Transform, Load) for a Genetic Epilepsy Diagnosis and Treatment Dashboard. In Medical Informatics Europe.
Prasetia, I. P. W., & Kurniawan, I. N. H. (2021). Data Warehouse Implementasi ETL (Extract, Transform, Load) pada Data warehouse Penjualan Menggunakan Tools Pentaho. TIERS Information Technology Journal, 2(1).
Pratama, I. P. A. E., & Permana, I. K. W. H. (2023). Analisa Pola Penjualan Berbasis Data Warehouse Menggunakan Metode ETL dan OLAP (Studi Kasus: Restoran Khayangan Kuliner). TEMATIK, 10(1), 124-130.
Rohajawati, S. (2024). Effectiveness of Digital Transformation in Data Warehouse Technology. The Indonesian Journal of Computer Science, 13(1).
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Desri Natalis Lasa, Ameiliani Dianira Barahama, Irene Realyta Haldy Trosi Tangkawarow (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
